Your agents are ready. The infrastructure to trust them at scale isn't.
Trellar is the layer that closes that gap.
The gap isn't capability. It's the absence of trust infrastructure.
Each step is only possible because of the one before it. Trellar is the operational infrastructure that makes the sequence work.
Full visibility into what every agent in your network is doing at runtime.
Enforce what each agent is and isn't allowed to do at runtime.
Confidence the system behaves as intended, backed by evidence.
Extend autonomy further, because now you have the ground truth to.
Platform teams running multi-agent systems in production already have observability. Logs, traces, exports, dashboards. What they don't have is a way to prove any given agent is safe enough to run with less oversight than it gets today, or a way to govern that isn't gated behind whoever on the team is technical enough to build it.
So autonomy stays throttled, not for lack of capability but for lack of a systematic way to build trust and a systematic way for every team, technical or not, to act on it.
The workaround most teams build is a patchwork of monitoring exports, custom scripts, periodic manual reviews, and hard limits on what agents are allowed to do, usually owned by whichever team has the engineering resources to build it. It prevents catastrophic failure. It doesn't build trust, and it doesn't scale past the team that built it.
Security and control plane tools restrict what agents can accomplish. That reduces risk, but it reduces capability at the same rate, which is the opposite of what teams running multi-agent systems actually need.
Trellar takes a different approach. It defines what each agent is authorized to do and monitors every run against that definition, so agents operate at full capacity within their boundaries instead of being boxed in by default. Trust is built from evidence, real runtime behavior, not assumptions, so when you're ready to extend autonomy, you have the ground truth to justify it.
Trust shouldn't depend on how technical your team is. Every team governs its own agents, in plain language, within its own scope, instead of waiting on whoever owns the tooling.
Think of it like onboarding a new hire. Close supervision early, easing off as trust is earned, with certain boundaries that never relax. The goal isn't permanent oversight. It's earning the right to reduce it.
Sits above any agent framework your team is already running. No replacement, no migration.
Behavioral baselines per agent. Health scores, latency rankings, and anomaly detection that fires before an incident.
A full, searchable timeline of every run, tool call, decision point, and LLM call, so you can trace an issue back to where it started.
Runtime control over what agents can do. Write rules directly, or upload policy docs and let Trellar translate them. Risk tolerance is yours to set.
Pauses agents at defined decision points, routes to the right person with full context, and resumes on approval. Escalation follows your team's structure, so it never becomes a bottleneck.
Feeds evaluations and escalation decisions back into the model, so behavior improves over time and human intervention drops as trust builds.
Query your entire agent network in plain language. See every agent, tool, and handoff mapped, and turn root-cause analysis into a conversation with the system instead of a manual dig through logs.
Governance has always defaulted to whoever has the most technical resources, which means everyone else waits. Compliance waiting on engineering for policy changes. Business owners waiting on platform teams to know what their agents are doing. Governance as a bottleneck instead of a foundation.
Trellar is built so every team governs its own agents, in its own scope, without depending on anyone else to translate for them. Write policy in plain language and Trellar enforces it. Set risk tolerance and escalation routing through the interface. Every new agent inherits a baseline of oversight the moment it connects, so no team starts from zero.
When everyone can act within their own scope, governance stops being a bottleneck and starts being an accelerator.
Works on top of the frameworks your team already runs
Trellar sits above your existing stack. No replacement, no migration, no changes to your orchestration code. If your agents are already running, Trellar activates on the first run.
No configuration sprint. No integration project. Trellar sits above your existing stack and starts delivering value on the first run.
Works above any framework you're already running
Baselines and evaluations build themselves automatically
See, control, and trust your agents from day one
Trellar operates outside your execution path, so there's no latency added to agent output and nothing to migrate or reconfigure in your existing stack.
Building and owning orchestration pipelines who need to see what agents are doing at runtime and debug failures without reconstructing runs from incomplete logs.
Who get asked "what happens when it fails?" and are tired of answering from exports and manual spot-checks they don't fully trust.
Accountable for what agents do in production, who need documented human oversight, audit trails, and enforcement records.
Watching working prototypes stall before production, needing the governance infrastructure to get them across the line.
Running agents that touch your workflows, but dependent on engineering to explain what they're doing and set the rules. Trellar gives you a direct view and direct controls, no technical translation required.
Building a multi-agent network was the heavy lift. Most of the value you built into it is still sitting on the table, held back by how much you can trust it to run on its own.
Extending autonomy is what turns that investment into ROI. Every task an agent can safely handle without a human in the loop is time and cost the network is already capable of saving. Trellar is what makes it safe to let that happen.
MVP is ready. We're selecting a small group of pilot partners. Tell us about your setup and we'll reach out within 3 business days.
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